🌌 StarGazer - MPI

StarGazer-MPI is a parallel application designed to count stars in astronomical images using distributed processing with MPI (Message Passing Interface). This tool splits images into blocks and distributes the workload across multiple processes, significantly speeding up the analysis of large datasets.

Table of Contents

• Prerequisites
• Usage
• Generating Histogram
• Help

Prerequisites

Before running the project, ensure you have the following installed:

• MPI (Message Passing Interface)
• Python 3
• pip
• GCC
• GNU Make

Usage

This project can be easily built using a makefile. Follow the commands below to compile and run the application:

⚠️ Commands must be executed in the root directory.

# Compile the MPI program
make

# Execute the program
make run p=<number_of_processes> img=<path/to/image.pgm> th=<threshold>

# Clean up the build
make clean

Generating Histogram

To help you choose the appropriate threshold value, you can generate a histogram plot (requires Python). Use the following commands:

# Build the Python virtual environment and install dependencies
make build

# Execute the histogram generation
make hist img=<path/to/image.pgm>

# Clean up the environment
make purge

Help

For additional help and available commands, run:

make help